Improving sentiment analysis of Arabic tweets

Abdulrahman Alruban; Muhammed Abduallah; Gueltoum Bendiab; Stavros Shiaeles; Marco Palomino

doi:10.1007/978-981-15-4825-3_12

Improving sentiment analysis of Arabic tweets

Abdulrahman Alruban, Muhammed Abduallah, Gueltoum Bendiab, Stavros Shiaeles^*, Marco Palomino

^*Corresponding author for this work

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

Twitter popularity grew rapidly the last years and become a place where people express their opinions, views, feelings and ideas. This popularity and the vast amount of information triggered the interest of companies as well as researchers on sentiment analysis trying to export meaningful results from this information. Even if there is a tremendous amount of work on Latin originated languages, such as English, there is not much research available on native languages such as Arabic, Greek etc. This research aims to develop a new system able to bridge the gap in Arabic users and sentiment analysis by providing a novel dictionary able to classify Arabic Tweets with different Arabic dialects and emotions, as positive, negative or natural. The study provides a quantitative analysis to gain an in-depth understanding of the phenomenon under investigation and the findings of the study show that the designed system is very promising.

Original language	English
Title of host publication	Security in Computing and Communications
Editors	Sabu M. Thampi, Gregorio Martinez Perez, Ryan Ko, Danda B. Rawat
Place of Publication	Singapore
Publisher	Springer
Pages	146-158
Number of pages	13
ISBN (Electronic)	978-981-15-4825-3
ISBN (Print)	978-981-15-4824-6
DOIs	https://doi.org/10.1007/978-981-15-4825-3_12
Publication status	Published - 26 Apr 2020
Event	7th International Symposium on Security in Computing and Communication - Trivandrum, India Duration: 18 Dec 2019 → 21 Dec 2019

Publication series

Name	Communications in Computer and Information Science
Publisher	Springer
Volume	1208
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	7th International Symposium on Security in Computing and Communication
Abbreviated title	SSCC 2019
Country/Territory	India
City	Trivandrum
Period	18/12/19 → 21/12/19

Access to Document

10.1007/978-981-15-4825-3_12

Arabic_sentiment_analysis_springer
his is a post-peer-review, pre-copyedit version of an article published in Security in Computing and Communications. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-981-15-4825-3_12.
Accepted author manuscript (Post-print), 178 KB

Cite this

@inproceedings{fa2cf5c4759f466994f11335e5f4f14a,

title = "Improving sentiment analysis of Arabic tweets",

abstract = "Twitter popularity grew rapidly the last years and become a place where people express their opinions, views, feelings and ideas. This popularity and the vast amount of information triggered the interest of companies as well as researchers on sentiment analysis trying to export meaningful results from this information. Even if there is a tremendous amount of work on Latin originated languages, such as English, there is not much research available on native languages such as Arabic, Greek etc. This research aims to develop a new system able to bridge the gap in Arabic users and sentiment analysis by providing a novel dictionary able to classify Arabic Tweets with different Arabic dialects and emotions, as positive, negative or natural. The study provides a quantitative analysis to gain an in-depth understanding of the phenomenon under investigation and the findings of the study show that the designed system is very promising.",

author = "Abdulrahman Alruban and Muhammed Abduallah and Gueltoum Bendiab and Stavros Shiaeles and Marco Palomino",

year = "2020",

month = apr,

day = "26",

doi = "10.1007/978-981-15-4825-3_12",

language = "English",

isbn = "978-981-15-4824-6",

series = "Communications in Computer and Information Science",

publisher = "Springer",

pages = "146--158",

editor = "Thampi, {Sabu M.} and {Martinez Perez}, Gregorio and Ryan Ko and Rawat, {Danda B.}",

booktitle = "Security in Computing and Communications",

note = "7th International Symposium on Security in Computing and Communication, SSCC 2019 ; Conference date: 18-12-2019 Through 21-12-2019",

}

Alruban, A, Abduallah, M, Bendiab, G, Shiaeles, S & Palomino, M 2020, Improving sentiment analysis of Arabic tweets. in SM Thampi, G Martinez Perez, R Ko & DB Rawat (eds), Security in Computing and Communications. Communications in Computer and Information Science, vol. 1208, Springer, Singapore, pp. 146-158, 7th International Symposium on Security in Computing and Communication, Trivandrum, India, 18/12/19. https://doi.org/10.1007/978-981-15-4825-3_12

Improving sentiment analysis of Arabic tweets. / Alruban, Abdulrahman; Abduallah, Muhammed; Bendiab, Gueltoum et al.
Security in Computing and Communications. ed. / Sabu M. Thampi; Gregorio Martinez Perez; Ryan Ko; Danda B. Rawat. Singapore: Springer, 2020. p. 146-158 (Communications in Computer and Information Science; Vol. 1208).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Improving sentiment analysis of Arabic tweets

AU - Alruban, Abdulrahman

AU - Abduallah, Muhammed

AU - Bendiab, Gueltoum

AU - Shiaeles, Stavros

AU - Palomino, Marco

PY - 2020/4/26

Y1 - 2020/4/26

N2 - Twitter popularity grew rapidly the last years and become a place where people express their opinions, views, feelings and ideas. This popularity and the vast amount of information triggered the interest of companies as well as researchers on sentiment analysis trying to export meaningful results from this information. Even if there is a tremendous amount of work on Latin originated languages, such as English, there is not much research available on native languages such as Arabic, Greek etc. This research aims to develop a new system able to bridge the gap in Arabic users and sentiment analysis by providing a novel dictionary able to classify Arabic Tweets with different Arabic dialects and emotions, as positive, negative or natural. The study provides a quantitative analysis to gain an in-depth understanding of the phenomenon under investigation and the findings of the study show that the designed system is very promising.

AB - Twitter popularity grew rapidly the last years and become a place where people express their opinions, views, feelings and ideas. This popularity and the vast amount of information triggered the interest of companies as well as researchers on sentiment analysis trying to export meaningful results from this information. Even if there is a tremendous amount of work on Latin originated languages, such as English, there is not much research available on native languages such as Arabic, Greek etc. This research aims to develop a new system able to bridge the gap in Arabic users and sentiment analysis by providing a novel dictionary able to classify Arabic Tweets with different Arabic dialects and emotions, as positive, negative or natural. The study provides a quantitative analysis to gain an in-depth understanding of the phenomenon under investigation and the findings of the study show that the designed system is very promising.

U2 - 10.1007/978-981-15-4825-3_12

DO - 10.1007/978-981-15-4825-3_12

M3 - Conference contribution

SN - 978-981-15-4824-6

T3 - Communications in Computer and Information Science

SP - 146

EP - 158

BT - Security in Computing and Communications

A2 - Thampi, Sabu M.

A2 - Martinez Perez, Gregorio

A2 - Ko, Ryan

A2 - Rawat, Danda B.

PB - Springer

CY - Singapore

T2 - 7th International Symposium on Security in Computing and Communication

Y2 - 18 December 2019 through 21 December 2019

ER -

Improving sentiment analysis of Arabic tweets

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